📄 quest.cwp.lib
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QUEST - Functions to ESTimate Quantiles:quest returns estimate - use when entire array is in memoryquestalloc returns quantile estimator - use before questupdatequestupdate updates and returns current estimate - use for large numbers of floats, too big to fit in memory at one timequestfree frees quantile estimatorquest:Input:p quantile to be estimated (0.0<=p<=1.0 is required)n number of samples in array x (n>=5 is required)x array[n] of floatsReturned: the estimate of a specified quantilequestalloc:Input:p quantile to be estimated (0.0<=p<=1.0 is required)n number of samples in array x (n>=5 is required)x array[n] of floatsReturned: pointer to a quantile estimatorquestupdate:Input:q pointer to quantile estimator (as returned by questalloc)n number of samples in array xx array[n] of floatsReturned: quantile estimatequestfree:q pointer to quantile estimator (as returned by questalloc)Notes:quest:The estimate should approach the sample quantile in the limit of large n.The estimate is most accurate for cumulative distribution functionsthat are smooth in the neighborhood of the quantile specified by p.This function is an implementation of the algorithm published byJain and Chlamtac (1985).questalloc:This function must be called before calling function questupdate.See also notes in questupdate.questupdate:The estimate should approach the sample quantile in the limit of large n.The estimate is most accurate for cumulative distribution functionsthat are smooth in the neighborhood of the quantile specified by p.This function is an implementation of the algorithm published byJain, R. and Chlamtac, I., 1985, The PP algorithm for dynamiccalculation of quantiles and histograms without storing observations:Comm. ACM, v. 28, n. 10.Reference:Jain, R. and Chlamtac, I., 1985, The PP algorithm for dynamiccalculation of quantiles and histograms without storing observations:Comm. ACM, v. 28, n. 10.Author: Dave Hale, Colorado School of Mines, 05/07/89
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